Objectives: To enhance the public awareness and facilitate diagnosis of osteoporosis, we aim to develop a new Chinese Osteoporosis Screening Algorithm (COSA) to identify people at high risk of osteoporosis. Methods: A total of 4747 postmenopausal women and men aged ! 50 from the Hong Kong Osteoporosis Study were randomly split into a development (N ¼ 2373) and an internal validation cohort (N ¼ 2374). An external validation cohort comprising 1876 community-dwelling subjects was used to evaluate the positive predictive value (PPV). Results: Among 11 predictors included, age, sex, weight, and history of fracture were significantly associated with osteoporosis after correction for multiple testing. Age- and sex-stratified models were developed due to the presence of significant sex and age interactions. The area under the curve of the COSA in the internal validation cohort was 0.761 (95% CI, 0.711e0.811), 0.822 (95% CI, 0.792e0.851), and 0.946 (95% CI, 0.908e0.984) for women aged < 65, women aged ! 65, and men, respectively. The COSA demonstrated improved reclassification performance when compared to Osteoporosis Self-Assessment Tool for Asians. In the external validation cohort, the PPV of COSA was 40.6%, 59.4%, and 19.4% forwomen aged < 65, women aged ! 65, and men, respectively. In addition, COSA > 0 was associated with an increased 10-year risk of hip fracture in women ! 65 (OR, 4.65; 95% CI, 2.24e9.65) and men (OR, 11.51; 95% CI, 4.16e31.81). Conclusions We have developed and validated a new osteoporosis screening algorithm, COSA, specific for Hong Kong Chinese.